LAUSR

Accurate identification of glycan structures is highly desirable as they are intimately linked to their different functions. However, glycan samples generally exist as mixtures with multiple isomeric structures, making assignment of individual glycan components very challenging, even with the aid of multistage mass spectrometry (MSn). Here, we present an approach, GIPS-mix, for assignment of isomeric glycans within a mixture using an intelligent group-opting strategy. Our approach enumerates all possible combinations (groupings) of candidate glycans and opts in the best-matched glycan group(s) based on the similarity between the simulated spectra of each glycan group and the acquired experimental spectra of the mixture. In the case that a single group could not be elected, a tie break is performed by additional MSn scanning using intelligently selected precursors. With 11 standard mixtures and 6 human milk oligosaccharide fractions, we demonstrate the application of GIPS-mix in assignment of individual glycans in mixtures with high accuracy and efficiency.